Linear Models and Generalizations : Least Squares and Alternatives
- Author
- C. Radhakrishna Rao, Shalabh, Helge Toutenburg, Christian Heumann
- Publication Year
- 2008
- Publisher
- Springer
- Language
- English
- Document Type
- Book
- Faculty / Subject Heading
- Mathematics and Statistics
- Download Book Read book
Gives an up-to-date account of the theory and applications of linear models. The book can be used as a text for courses in statistics at the graduate level and as an accompanying text for courses in other areas. Some of the highlights in this book are as follows. A relatively extensive chapter on matrix theory (Appendix A) provides the necessary tools for proving theorems discussed in the text and offers a selection of classical and modern algebraic results that are useful in research work in econometrics, engineering, and optimization theory. The matrix theory of the last ten years has produced a series of fundamental results aboutthe de?niteness ofmatrices,especially forthe di?erences ofmatrices, which enable superiority comparisons of two biased estimates to be made for the ?rst time. We have attempted to provide a uni?ed theory of inference from linear models with minimal assumptions
Keywords: Mathematics and Statistics / Fitting / Generalized linear model / Least Squares / Likelihood / Optimization Theory / Regression / Best fit / Calculus / Econometrics / Linear regression / Optimization / Statistics
